Practice Term Frequency – Inverse Document Frequency (TF-IDF) - 9.4.2 | 9. Natural Language Processing (NLP) | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does TF stand for?

💡 Hint: It's the first part of TF-IDF.

Question 2

Easy

What does IDF measure?

💡 Hint: Think of the word 'Inverse' in IDF.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does TF-IDF measure?

  • The frequency of a word
  • Word importance in a document
  • Document length

💡 Hint: Think about why we analyze text.

Question 2

True or False: High IDF suggests a term is common across documents.

  • True
  • False

💡 Hint: Focus on the meaning of 'Inverse'.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You have 5 documents and the term 'machine' appears in 3. Calculate its IDF and TF given it appears 4 times in a document of 200 words.

💡 Hint: Calculate IDF, then TF, and multiply them.

Question 2

If a term appears in every document of a dataset and its TF is high, what does that imply about its IDF?

💡 Hint: Consider why commonality affects uniqueness.

Challenge and get performance evaluation